A numerical investigation on height anomaly prediction in mountainous areas
A numerical investigation on height anomaly prediction in mountainous areas
复制标题
山区高度异常预报的数值研究
DOI：
10.1007/bf00815483
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发表时间：
1995
期刊：
影响因子：
--
通讯作者：
K. Schwarz
中科院分区：
文献类型：
--
作者：
Ye Cai Li;M. Sideris;K. Schwarz
本文给出了用Molodensky边值问题的解预测高度异常的数值实例。计算是在加拿大落基山脉的两个地区进行的。使用的数据在网格上，网格间距从100米到5弧分不等。数值结果表明，在重力插值中应采用布格异常或地形均衡重力异常。如果使用足够密集的数据网格，预测山区高度异常的精度达到10 cm （1σ）是可行的。消除系统偏差后，在50个基准上，当格距为1km时，高程异常与GPS/水准测量的大地水准面波动差为12 cm (1σ)，当格距为5′时，高程异常与GPS/水准测量的大地水准面波动差为50 cm （1σ）。在大多数情况下，网格间距不需要小于1 km，因为当网格间距从100 m增加到1000 m时，高度异常只变化了3 cm （1σ）。数值结果还表明，除了极端情况外，在所有情况下都只需要计算Molodensky级数的前两项，因为与客观精度相比，高阶项的贡献可以忽略不计。
This paper provides numerical examples for the prediction of height anomalies by the solution of Molodensky's boundary value problem. Computations are done within two areas in the Canadian Rockies. The data used are on a grid with various grid spacings from 100 m to 5 arc-minutes. Numerical results indicate that the Bouguer or the topographicisostatic gravity anomalies should be used in gravity interpolation. It is feasible to predict height anomalies in mountainous areas with an accuracy of 10 cm (1σ) if sufficiently dense data grids are used. After removing the systematic bias, the differences between the geoid undulations converted from height anomalies and those derived from GPS/levelling on 50 benchmarks is 12 cm (1σ) when the grid spacing is 1km, and 50 cm (1σ) when the grid spacing is 5′. It is not necessary, in most cases, to require a grid spacing finer than 1 km, because the height anomaly changes only by 3 cm (1σ) when the grid spacing is increased from 100 m to 1000 m. Numerical results also indicate that, only the first two terms of the Molodensky series have to be evaluated in all but the extreme cases, since the contributions of the higher order terms are negligible compared to the objective accuracy.